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CALL FOR PARTICIPATION: CHEMDNER task: Chemical compound and drug
name recognition task
(http://www.biocreative.org/tasks/biocreative-iv/chemdner)
(1) TASK GOAL AND MOTIVATION
The goal of this task is to promote the implementation of systems
that are able to detect mentions in text of chemical compounds
and drugs. The recognition of chemical entities is also crucial
for other subsequent text processing strategies, such as
detection of drug-protein interactions, adverse effects of
chemical compounds or the extraction of pathway and metabolic
reaction relations. A range of different methods have been
explored for the recognition of chemical compound mentions
including machine learning based approaches, rule-based systems
and different types of dictionary-lookup strategies.
We foresee a considerable interest in the result of this task by
the NLP/text mining community on one side, as well as by the
bioinformatics, drug discovery/biomedicine and chemoinformatics
communities on the other side. As has been the case in previous
BioCreative efforts (resulting in high impact papers in the
field), we expect that successful participants will have the
opportunity to publish their system descriptions in a journal
article.
(2) CHEMDNER TRACK DESCRIPTION
The CHEMDNER is one of the tracks posed at the BioCreative IV
community challenge (http://www.biocreative.org).
We invite participants to submit results for the CHEMDNER task
providing predictions for one or both of the following subtasks:
a) Given a set of documents, return for each of them a ranked
list of chemical entities described within each of these
documents [Chemical document indexing sub-task]
b) Provide for a given document the start and end indices
corresponding to all the chemical entities mentioned in this
document [Chemical entity mention recognition sub-task].
For these two tasks the organizers will release training and test
data collections. The task organizers will provide details on the
used annotation guidelines; define a list of criteria for
relevant chemical compound entity types as well as selection of
documents for annotation.
(3) REGISTRATION
Teams can participate in the CHEMDNER task by registering for
track 2 of BioCreative IV. You can register additionally for
other tracks too. To register your team, go to the following page
that provides more detailed instructions:
http://www.biocreative.org/news/biocreative-iv/team/
Mailing list and contact information:
You can post questions related to the CHEMDNER task to the
BioCreative mailing list. To register for the BioCreative mailing
list, please visit the following page:
http://biocreative.sourceforge.net/mailing.html
(4) WORKSHOP
CHEMDNER is part of the BioCreative evaluation effort. The
BioCreative Organizing Committee will host the BioCreative IV
Challenge evaluation workshop
(http://www.biocreative.org/events/biocreative-iv/CFP/) at NCBI,
National Institutes of
Health, Bethesda, Maryland, on October 7-9, 2013
(5) CHEMDNER TASK ORGANIZERS
Martin Krallinger, Spanish National Cancer Research Center (CNIO)
Obdulia Rabal, University of Navarra, Spain
Julen Oyarzabal, University of Navarra, Spain
Alfonso Valencia, Spanish National Cancer Research Center (CNIO)
(6) REFERENCES
- Vazquez, M., Krallinger, M., Leitner, F., & Valencia, A.
(2011). Text Mining for Drugs and Chemical Compounds: Methods,
Tools and Applications. Molecular Informatics, 30(6-7),
506-519.
- Corbett, P., Batchelor, C., & Teufel, S. (2007). Annotation of
chemical named entities. BioNLP 2007: Biological,
translational, and clinical language processing, 57-64.
- Klinger, R., Kolárik, C., Fluck, J., Hofmann-Apitius, M., &
Friedrich, C. M. (2008). Detection of IUPAC and IUPAC-like
chemical names. Bioinformatics, 24(13), i268-i276.
- Hettne, K. M., Stierum, R. H., Schuemie, M. J., Hendriksen, P.
J., Schijvenaars, B. J., Mulligen, E. M. V., ... & Kors, J. A.
(2009). A dictionary to identify small molecules and drugs in
free text. Bioinformatics, 25(22), 2983-2991.
- Yeh, A., Morgan, A., Colosimo, M., & Hirschman, L. (2005).
BioCreAtIvE task 1A: gene mention finding evaluation. BMC
bioinformatics, 6(Suppl 1), S2.
- Smith, L., Tanabe, L. K., Ando, R. J., Kuo, C. J., Chung, I.
F., Hsu, C. N., ... & Wilbur, W. J. (2008). Overview of
BioCreative II gene mention recognition. Genome Biology,
9(Suppl 2), S2.
ATT00001
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